Felipe Sierra

7.5k total citations · 3 hit papers
90 papers, 4.7k citations indexed

About

Felipe Sierra is a scholar working on Molecular Biology, Aging and Physiology. According to data from OpenAlex, Felipe Sierra has authored 90 papers receiving a total of 4.7k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Molecular Biology, 20 papers in Aging and 17 papers in Physiology. Recurrent topics in Felipe Sierra's work include Genetics, Aging, and Longevity in Model Organisms (20 papers), Coagulation, Bradykinin, Polyphosphates, and Angioedema (12 papers) and Mast cells and histamine (7 papers). Felipe Sierra is often cited by papers focused on Genetics, Aging, and Longevity in Model Organisms (20 papers), Coagulation, Bradykinin, Polyphosphates, and Angioedema (12 papers) and Mast cells and histamine (7 papers). Felipe Sierra collaborates with scholars based in United States, Chile and Canada. Felipe Sierra's co-authors include Tony Wyss‐Coray, Judith Campisi, Thomas A. Rando, Brian K. Kennedy, Gordon J. Lithgow, Ana María Cuervo, Arlan Richardson, Richard I. Morimoto, Eric E. Schadt and Elissa S. Epel and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Felipe Sierra

86 papers receiving 4.6k citations

Hit Papers

Geroscience: Linking Aging to Chronic Disease 2014 2026 2018 2022 2014 2019 2025 500 1000 1.5k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Felipe Sierra United States 27 1.8k 1.4k 879 481 464 90 4.7k
Daniela Mari Italy 44 2.3k 1.3× 1.5k 1.1× 813 0.9× 372 0.8× 519 1.1× 170 6.2k
Annibale Alessandro Puca Italy 38 2.2k 1.2× 1.2k 0.8× 1.2k 1.4× 320 0.7× 430 0.9× 127 5.1k
Cristina Giuliani Italy 26 2.0k 1.1× 1.1k 0.8× 407 0.5× 200 0.4× 613 1.3× 89 4.4k
Diana van Heemst Netherlands 46 2.1k 1.2× 2.4k 1.7× 1.1k 1.3× 306 0.6× 357 0.8× 221 7.2k
Carmen Martín-Ruiz United Kingdom 43 2.2k 1.2× 3.5k 2.5× 925 1.1× 740 1.5× 731 1.6× 98 7.1k
Vladimir N. Anisimov Russia 39 2.5k 1.4× 1.8k 1.3× 1.4k 1.6× 305 0.6× 172 0.4× 235 5.9k
Morten Scheibye‐Knudsen Denmark 33 2.7k 1.5× 1.3k 0.9× 548 0.6× 478 1.0× 225 0.5× 64 5.2k
Toshiko Tanaka United States 38 1.5k 0.8× 1.6k 1.2× 345 0.4× 456 0.9× 274 0.6× 178 5.0k
Jorge D. Erusalimsky United Kingdom 39 3.4k 1.9× 3.2k 2.3× 540 0.6× 327 0.7× 1.2k 2.6× 87 8.0k
Martijn E.T. Dollé Netherlands 39 3.1k 1.7× 1.8k 1.3× 811 0.9× 130 0.3× 607 1.3× 115 5.8k

Countries citing papers authored by Felipe Sierra

Since Specialization
Citations

This map shows the geographic impact of Felipe Sierra's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Felipe Sierra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Felipe Sierra more than expected).

Fields of papers citing papers by Felipe Sierra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Felipe Sierra. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Felipe Sierra. The network helps show where Felipe Sierra may publish in the future.

Co-authorship network of co-authors of Felipe Sierra

This figure shows the co-authorship network connecting the top 25 collaborators of Felipe Sierra. A scholar is included among the top collaborators of Felipe Sierra based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Felipe Sierra. Felipe Sierra is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Kroemer, Guido, Andrea B. Maier, Ana María Cuervo, et al.. (2025). From geroscience to precision geromedicine: Understanding and managing aging. Cell. 188(8). 2043–2062. 61 indexed citations breakdown →
2.
Espinoza, Ignacio, et al.. (2024). Temporomandibular joint study by magnetic resonance imaging: it is time to inform. SHILAP Revista de lepidopterología. 30(3).
3.
Sierra, Felipe, et al.. (2023). The Role of the National Institute on Aging in the Development of the Field of Geroscience. Cold Spring Harbor Perspectives in Medicine. 13(10). a041211–a041211. 6 indexed citations
4.
Barreto, Philipe de Souto, Yves Rolland, Luigi Ferrucci, et al.. (2023). Looking at frailty and intrinsic capacity through a geroscience lens: the ICFSR & Geroscience Task Force. Nature Aging. 3(12). 1474–1479. 15 indexed citations
5.
Takeda, Catherine, Davide Angioni, Philipe de Souto Barreto, et al.. (2020). Age-Related Frailty: A Clinical Model for Geroscience?. The journal of nutrition health & aging. 24(10). 1140–1143. 20 indexed citations
6.
Sierra, Felipe. (2020). Geroscience and the Role of Aging in the Etiology and Management of Alzheimer's Disease. The Journal of Prevention of Alzheimer s Disease. 7(1). 2–3. 14 indexed citations
7.
Kirkland, James L., Michael B. Stout, & Felipe Sierra. (2016). Resilience in Aging Mice. The Journals of Gerontology Series A. 71(11). 1407–1414. 58 indexed citations
8.
Richardson, Arlan, Kathleen E. Fischer, John R. Speakman, et al.. (2015). Measures of Healthspan as Indices of Aging in Mice—A Recommendation. The Journals of Gerontology Series A. 71(4). 427–430. 63 indexed citations
9.
Burch, James B., Alison D. Augustine, Lex Frieden, et al.. (2014). Advances in Geroscience: Impact on Healthspan and Chronic Disease. The Journals of Gerontology Series A. 69(Suppl 1). S1–S3. 134 indexed citations
10.
Kennedy, Brian K., Shelley L. Berger, Anne Brunet, et al.. (2014). Geroscience: Linking Aging to Chronic Disease. Cell. 159(4). 709–713. 1717 indexed citations breakdown →
11.
Perez, Carlos A., et al.. (2008). Diminished Acute Phase Response and Increased Hepatic Inflammation of Aged Rats in Response to Intraperitoneal Injection of Lipopolysaccharide. The Journals of Gerontology Series A. 63(12). 1299–1306. 9 indexed citations
12.
Acuña‐Castillo, Claudio, Elías Leiva‐Salcedo, Viviana Pérez, et al.. (2005). T-kininogen, a cystatin-like molecule, inhibits ERK-dependent lymphocyte proliferation. Mechanisms of Ageing and Development. 126(12). 1284–1291. 15 indexed citations
13.
Torres, Claudio, et al.. (2002). Defect in ERK2 and p54JNK Activation in Aging Mouse Splenocytes. The Journals of Gerontology Series A. 57(2). B41–B47. 11 indexed citations
14.
Torres, Claudio, et al.. (2001). Modulation of the ERK pathway of signal transduction by cysteine proteinase inhibitors. Journal of Cellular Biochemistry. 80(1). 11–23. 2 indexed citations
15.
Torres, Claudio, et al.. (2001). T-Kininogen Inhibits Fibroblast Proliferation in the G1 Phase of the Cell Cycle. Experimental Cell Research. 269(2). 171–179. 10 indexed citations
16.
Torres, Claudio, et al.. (2000). Modulation of the ERK pathway of signal transduction by cysteine proteinase inhibitors. Journal of Cellular Biochemistry. 80(1). 11–23. 18 indexed citations
17.
Sierra, Felipe, et al.. (1998). Changes in Hepatic DNA Binding Proteins as a Function of Age in Rats. The Journals of Gerontology Series A. 53A(2). B102–B110. 9 indexed citations
18.
Keppler, Daniel, Bernard Sordat, & Felipe Sierra. (1997). T-Kininogen present in the liver of old rats is biologically active and readily forms complexes with endogenous cysteine proteinases. Mechanisms of Ageing and Development. 98(2). 151–165. 8 indexed citations
19.
20.
Sierra, Felipe, et al.. (1992). Serum T‐Kininogen Levels Increase Shortly before Death. Annals of the New York Academy of Sciences. 663(1). 479–480. 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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